Investigating Contextual Variations in Aviation Social Intention Recognition: A Scenario Design Framework for Evaluating Intelligent Systems
Omer Arslan (TU Delft - Electrical Engineering, Mathematics and Computer Science)
H.S. Hung – Mentor (TU Delft - Pattern Recognition and Bioinformatics)
V. Popov – Mentor (TU Delft - Pattern Recognition and Bioinformatics)
A. Mercier – Mentor (TU Delft - Pattern Recognition and Bioinformatics)
R. Guerra Marroquim – Graduation committee member (TU Delft - Computer Graphics and Visualisation)
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Abstract
The design of data collection scenarios is critical for evaluating intelligent systems for social intention recognition in aviation. Identical aircraft behaviors can generate multiple equally plausible intention interpretations depending on situational context and the observer’s professional perspective, yet existing research offers limited guidance for constructing scenarios that preserve this interpretive open-endedness. This study addresses this gap through an exploratory, literature-based investigation of how contextual factors shape intention interpretation across aviation roles. An integrated framework combining the 3Cs model of situational analysis and script theory is proposed to identify contextual dimensions influencing interpretation. Through qualitative synthesis of aviation literature, the framework demonstrates how variations in cues, classes, characteristics, and internal-external script configurations can produce divergent but valid intention narratives for the same observable behavior. The resulting scenario-first methodology provides structured guidance for designing aviation scenarios that support role-dependent intention annotation and evaluate intelligent systems. As a conceptual contribution, the framework requires empirical validation by aviation professionals.